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The loss of ship propulsive power has been recognised as the most frequently occurring incident at sea. Given the fact that the manoeuvrability of a ship is highly reliant on the propulsive power produced by a rotating propeller, propulsion loss may pose potential threats to navigational safety in a real seaway by resulting in further serious incidents, such as collision, contact, and grounding. The key objective of this paper is to analyse the propulsion loss impacts on the turning capability of the KRISO Container Ship (KCS) model in different wave height conditions, using unsteady Reynolds-Averaged Navier-Stokes (URANS) computations. It is expected that this work will be of great interest to Master Mariners and navigating officers who are in charge of ship handling and help enhance navigational safety in real sea states.

ABSTRACTThis study details an extensive investigation into the nearfield longitudinal wake profiles of a high-speed planing hull. Developing understanding this flow is benaficial to the designers of stepped hulls in determining how the forebody’s wake intersects with the afterbody. As no experimental data was available, a novel small-scale model-testing programme was undertaken, measuring Centreline (CL) and Quarter Beam (QB) nearfield longitudinal wake profiles, as well as the forces. The nearfield wake profile was found to exhibit trends in agreement with the findings of studies investigating the mid and far-field wake. The results of this experimental work are provided in full as validation data. Savitsky’s Wake Equations and the Linear Wake Assumption are then assessed to determine the level of confidence with which they may be used to model this flow. Savitsky’s Wake Equations displayed a surprising level of accuracy whereas the Linear Wake Assumption was invalid for the conditions investigated.

The ship hull form optimization using the Computational Fluid Dynamics (CFD) method is increasingly employed in the early design of a ship, as an optimal ship hull form can obtain good hydrodynamics. However, it is time-consuming due to its many CFD simulations for the optimization. This paper presents a ship hull form optimization loop using the surrogate model, deep belief network (DBN), to reduce the wave-making resistance of the Wigley ship. The prediction performance of the wave-making resistance of the Wigley ship using the DBN method is discussed and compared with the traditional surrogate models found in this study. The results show that the resistance obtained using the deep belief network algorithm is superior to that obtained using the typical surrogate models. Then, a ship hull form optimization framework is built by integrating the Free From Deformation, non-linear programming by quadratic Lagrangian and deep belief network algorithms. The optimization results show that the deep belief network-based ship hull form optimization loop can be used to optimize the Wigley ship. The study presented in this paper could provide a deep learning algorithm for the ship design optimization.

The problem of predicting a ship’s form factor and associated scale effects has been subject to many investigations in recent years. In this study, an attempt is made to investigate whether the form factor is influenced by a change in the ship’s speed by numerically modelling a geosim series of the KCS hull form by means of a RANS solver. The turbulence dependence of the problem is also studied by altering the closure model among three widely used approaches (the k-ω, k-ω SST,and k-εmodels). The results show that at very low speeds (Froude numbers in the range of 0.02–0.06) the numerical model predicts changes in the form factor of a ship between 10% and 20%, depending on the turbulence model and scale factor choices. As the speed is increased further, the form factor exhibits little change, usually in the range of 1% or less. Simulations where the Reynolds number is changed by approximately two orders of magnitude, achieved by altering the value of viscosity, confirmed that the form factor can be considered Froude-dependent only for low speeds, predicting essentially identical values when high speed cases are considered.

Seakeeping, especially for the roll motions, is of critical importance to the safe operation of fishing boats in Indonesia. In this study, a traditional East Java Fishing Boat (EJFB) has been analysed in terms of its seakeeping performance. Furthermore, a bilge keel was designed to reduce the roll motions of the EJFB using multiple stages approach. After installing the designed bilge keels, it was shown that up to 11.78% and 4.87% reduction in the roll response of irregular seaways and the total resistance under the design speed, respectively. It was concluded that the roll-stabilized-EJFB will enhance the well-being of the fisherman and contribute to the boats' safe operation, especially in extreme weather conditions. Moreover, the total resistance reduction of the EJFB due to the installation of the designed bilge keels also resulted in increased operational efficiency and reduced fuel costs and fuel emissions for local stakeholders.

ABSTRACTWith the rapid development of the computational technology, computational fluid dynamics (CFD) tools have been widely used to evaluate the ship hydrodynamic performances in the hull forms optimization. However, it is very time consuming since a great number of the CFD simulations need to be performed for one single optimization. It is of great importance to find a high-effective method to replace the calculation of the CFD tools. In this study, a CFD-based hull form optimization loop has been developed by integrating an approximate method to optimize hull form for reducing the total resistance in calm water. In order to improve the optimization accuracy of particle swarm optimization (PSO) algorithm, an improved PSO (IPSO) algorithm is presented where the inertia weight coefficient and search method are designed based on random inertia weight and convergence evaluation, respectively. To improve the prediction accuracy of total resistance, a data prediction method based on IPSO-Elman neural network (NN) is proposed. Herein, IPSO algorithm is used to train the weight coefficients and self-feedback gain coefficient of ElmanNN. In order to build IPSO-ElmanNN model, optimal Latin hypercube design (Opt LHD) is used to design the sampling hull forms, and the total resistance (objective function) of these hull forms are calculated by Reynolds averaged Navier–Stokes (RANS) method. For the purpose of this article, this optimization framework has been employed to optimize two ships, namely, the DTMB5512 and WIGLEY III, and these hull forms are changed by arbitrary shape deformation (ASD) technique. The results show that the optimization framework developed in this study can be used to optimize hull forms with significantly reduced computational effort.

In order to reduce the total resistance of a hull, an optimization framework for the bulbous bow optimization was presented. The total resistance in calm water was selected as the objective function, and the overset mesh technique was used for mesh generation. RANS method was used to calculate the total resistance of the hull. In order to improve the efficiency and smoothness of the geometric reconstruction, the arbitrary shape deformation (ASD) technique was introduced to change the shape of the bulbous bow. To improve the global search ability of the particle swarm optimization (PSO) algorithm, an improved particle swarm optimization (IPSO) algorithm was proposed to set up the optimization model. After a series of optimization analyses, the optimal hull form was found. It can be concluded that the simulation based design framework built in this paper is a promising method for bulbous bow optimization.

The slow steaming approach is increasing in popularity for commercial vessels, as it provides a method of reducing fuel use, and therefore operating costs, in the current economic climate. It is very important to be able to evaluate a ship's response to waves, because any added resistance or loss of speed may cause delays or course alterations, leading to financial losses. Potential flow theory based linear strip theory is still a widely used method among naval architects, due to its fast solutions with sufficient engineering accuracy. The key objective of this study is to predict the ship motions and added resistance of the S-175 containership, and to estimate the increase in effective power and fuel consumption due to its operation in regular and irregular head seas. The analyses were performed at design and slow steaming speeds, for a range of wave conditions in regular seas, and for three different sea states in irregular seas. The results obtained at a ship speed corresponding to Froude number 0.25 were compared to available experimental data and were found to be in good agreement with the experiments. The numerical analyses were carried out using VERES, which is based on potential flow theory.

An extensive series of towing tests using flat plates covered with artificial barnacles were carried out at the Kelvin Hydrodynamics Laboratory (KHL) at the University of Strathclyde. The tests were designed to examine the effect of the coverage percentage of barnacles on the resistance and effective power of ships, over a range of Reynolds numbers.

The loss of ship propulsion has been reported to be the most frequent cause of accidents at sea over the last few years. The loss of propulsive power has a notable effect on the behaviour of a ship during ship manoeuvring, and hence the manoeuvrability of ships suffering from propulsion loss should be accurately estimated for navigation safety. The aim of this study is to evaluate the effects of a propulsion failure on the manoeuvrability of the KRISO Container Ship (KCS) using a fully nonlinear URANS model, which is capable of resolving complex fluid-structure interactions with high accuracy. A series of case studies were carried out to compare the ship performances of both the normal and propulsion loss condition, especially for the course keeping and turning circle manoeuvres. The results explicitly revealed that the propulsion failure has a strong influence on the ship manoeuvrability, implying the importance of sufficient propulsion power when vessels are underway. The key findings obtained from this study are believed to provide navigators with a practical insight into ship manoeuvrability under the propulsion failure condition as well as contribute to developing standards for navigational safety in waves.

Vessels can operate in unpredictable environments depending on the geographical area and weather conditions. One example of conditions a vessel might not be assessed against is the presence of depth-varying currents, which are particularly relevant in confined waters where currents can be created due to tidal influences, or short fetches in inland waterways. The possible presence of depth-varying currents motivates a numerical assessment of the effects of sheared currents on the hydrodynamic performance of the KRISO Container Ship (KCS) in confined waters. The results highlight that exploiting currents, such as those generated by tides could be used to improve the energy efficiency of vessels considerably. These currents present significant possibilities for voyage optimisation based on geographical and meteorological conditions. The results specific for the KRISO container ship point to resistance reductions when the current assists ship motions, accompanied by considerable decreases in sinkage and trim. Conversely, when currents oppose ship motion, resistance, sinkage and trim can increase by a factor of 3 depending on the strength and shape of the depth-varying current. The results also show that a current with constant vorticity, a case frequently used in the literature to investigate the impact of sheared currents, creates the biggest increase and decrease for inhibiting and assisting currents, respectively.